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Social prediction: a new research paradigm based on machine learning

Chen, Yunsong, Wu, Xiaogang, Hu, Anning, He, Guangye and Ju, Guodong (2021) Social prediction: a new research paradigm based on machine learning. Journal of Chinese Sociology, 8 (1). ISSN 2198-2635

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Identification Number: 10.1186/s40711-021-00152-z

Abstract

Sociology is a science concerned with both the interpretive understanding of social action and the corresponding causal explanation, process, and result. A causal explanation should be the foundation of prediction. For many years, due to data and computing power constraints, quantitative research in social science has primarily focused on statistical tests to analyze correlations and causality, leaving predictions largely ignored. By sorting out the historical context of "social prediction," this article redefines this concept by introducing why and how machine learning can help prediction in a scientific way. Furthermore, this article summarizes the academic value and governance value of social prediction and suggests that it is a potential breakthrough in the contemporary social research paradigm. We believe that through machine learning, we can witness the advent of an era of a paradigm shift from correlation and causality to social prediction. This shift will provide a rare opportunity for sociology in China to become the international frontier of computational social sciences and accelerate the construction of philosophy and social science with Chinese characteristics.

Item Type: Article
Official URL: https://journalofchinesesociology.springeropen.com...
Additional Information: © 2021 The Authors
Divisions: Social Policy
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date Deposited: 08 Sep 2021 14:21
Last Modified: 20 Oct 2021 03:01
URI: http://eprints.lse.ac.uk/id/eprint/111876

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